Biblio

The Advanced Encryption Standard (AES) enables secure transmission of confidential messages. Since its invention, there have been many proposed attacks against the scheme. For example, one can inject errors or faults to acquire the encryption keys. It has been shown that the AES algorithm itself does not provide a protection against these types of attacks. Therefore, additional techniques like error control codes (ECCs) have been proposed to detect active attacks. However, not all the proposed solutions show the adequate efficacy. For instance, linear ECCs have some critical limitations, especially when the injected errors are beyond their fault detection or tolerance capabilities. In this paper, we propose a new method based on a non-linear code to protect all four internal stages of the AES hardware implementation. With this method, the protected AES system is able to (a) detect all multiplicity of errors with a high probability and (b) correct them if the errors follow certain patterns or frequencies. Results shows that the proposed method provides much higher security and reliability to the AES hardware implementation with minimal overhead.

Voice assistants like Siri enable us to control IoT devices conveniently with voice commands, however, they also provide new attack opportunities for adversaries. Previous papers attack voice assistants with obfuscated voice commands by leveraging the gap between speech recognition system and human voice perception. The limitation is that these obfuscated commands are audible and thus conspicuous to device owners. In this poster, we propose a novel mechanism to directly attack the microphone used for sensing voice data with inaudible voice commands. We show that the adversary can exploit the microphone's non-linearity and play well-designed inaudible ultrasounds to cause the microphone to record normal voice commands, and thus control the victim device inconspicuously. We demonstrate via end-to-end real-world experiments that our inaudible voice commands can attack an Android phone and an Amazon Echo device with high success rates at a range of 2-3 meters.